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Unverified Commit 4642bc52 authored by Laurent Modolo's avatar Laurent Modolo
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0_1_Clone_size.R: change points size for clone_diversity plot

parent f0e1cbc9
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......@@ -548,44 +548,50 @@ data %>%
# abs number of cells
clone
data <- clone %>%
data <- clone %>%
mutate(day = fct_reorder(day, as.numeric(as.vector(day)))) %>%
group_by(donor, day, antigen) %>%
select(-percent) %>%
mutate(day_size = n()) %>%
group_by(donor, antigen) %>%
mutate(days_size = max(day_size)) %>%
group_by(donor, day, antigen) %>%
nest() %>%
mutate(detected_clone = lapply(data, function(data){
n_sample <- 1000
n_sample <- 20
tibble(
n_cell = seq(
from = 100,
to = max(500, nrow(data) + 10),
step = 1) %>%
from = 10,
to = max(500, (data %>% pull(days_size) %>% max()) + 10),
by = 1) %>%
rep(n_sample),
sample = rep(
1:n_sample,
each = (
seq(
from = 100,
to = max(500, nrow(data) + 10),
step = 1) %>%
from = 10,
to = max(500, (data %>% pull(days_size) %>% max()) + 10),
by = 1) %>%
length()
)),
day_size = nrow(data)
day_size = (data %>% pull(day_size) %>% max()),
days_size = (data %>% pull(days_size) %>% max())
) %>%
mutate(
detected_clone = pbmcapply::pbmclapply(n_cell, function(n_cell, data){
data %>%
select(clone) %>%
data %>%
select(clone) %>%
.[sample(1:nrow(.), round(n_cell), replace = T), ] %>%
distinct() %>%
distinct() %>%
nrow()
}, data = data,
mc.cores = 10,
ignore.interactive = T) %>% unlist(),
day_clone = data %>%
select(clone) %>%
distinct() %>%
},
data = data,
mc.cores = 10,
ignore.interactive = T
) %>% unlist(),
day_clone = data %>%
select(clone) %>%
distinct() %>%
nrow()
)
}
......@@ -596,7 +602,7 @@ data <- clone %>%
) %>%
group_by(donor, antigen, n_cell) %>%
nest() %>%
mutate(pval = lapply(data, function(data){
mutate(pval = pbmcapply::pbmclapply(data, function(data){
data %>%
group_by(day) %>%
mutate(
......@@ -613,17 +619,21 @@ data <- clone %>%
mutate(pval = max(sum(s_ecdf))) %>%
pull(pval) %>%
max()
})) %>%
},
mc.cores = 10,
ignore.interactive = T)) %>%
unnest(data, pval) %>%
group_by(donor, antigen) %>%
mutate(pval_signif = max(n_cell[pval > 0.05])) %>%
select(-data)
save(data, file = "results/2020_10_30_clone_diversity_bootstrap.Rdata")
save(data, file = "results/2020_11_01_clone_diversity_bootstrap.Rdata")
load(file = "results/2020_11_01_clone_diversity_bootstrap.Rdata")
p <- ggplot(data %>%
filter(n_cell < max(pval_signif, day_size))) +
filter(n_cell < max(pval_signif, days_size))) +
geom_vline(
aes(
xintercept = pval_signif
......@@ -632,7 +642,7 @@ p <- ggplot(data %>%
linetype = 1,
size = 1.5
) +
geom_line(data = data %>%
geom_point(data = data %>%
filter(n_cell < day_size),
aes(
x = n_cell,
......@@ -640,9 +650,10 @@ p <- ggplot(data %>%
color = day,
group = str_c(sample, day)
),
alpha = 0.1,
binwidth = c(1, 1),
alpha = 0.01
) +
scale_fill_viridis_d() +
# scale_fill_viridis_d() +
geom_smooth(data = data %>%
filter(n_cell < max(pval_signif, day_size) + 10),
aes(
......@@ -658,9 +669,10 @@ p <- ggplot(data %>%
labs(x = "number of cells",
y = "number of clone detected") +
guides(colour = guide_legend(override.aes = list(alpha = 1))) +
facet_wrap(~ antigen + donor, scales = "free", ncol = 4)
facet_wrap(~ antigen + donor, scales = "free", ncol = 4) +
theme_classic()
ggsave(plot = p, filename = "results/2020_10_30_clone_diversity_bootstrap.png", width = 30, height = 15, units = "cm")
ggsave(plot = p, filename = "results/2020_10_30_clone_diversity_bootstrap.pdf", width = 30, height = 15, units = "cm")
ggsave(plot = p, filename = "results/2020_11_05_clone_diversity_bootstrap.pdf", width = 30, height = 15, units = "cm")
ggsave(plot = p, filename = "results/2020_11_05_clone_diversity_bootstrap.png", width = 30, height = 15, units = "cm")
load(file = "results/2020_10_29_clone_diversity_bootstrap.Rdata")
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